Another regular season is underway as teams—fresh from spring training—dive head first into a sea of possibilities: will the Cubs win a World Series this year? How about those Mariners? Who will be this year's Hall of Famers? For fans, another question is increasingly becoming the subject of bar room chatter: which team will be hacked this season?

A Game of Numbers

Back in January of this year, former St. Louis Cardinals scouting director Chris Correa pleaded guilty to five of 12 charges in the 2014 hacking case of rival's Houston Astros' computer network and proprietary player database Ground Control. We covered the Cardinals/Astros hack in-depth last year; this year, it's anyone's guess as to which rivals will be splashed across the data breach headlines next. Save for a handful of teams, most of the MLB these days are employing a staff of sabermetrians and data scientists to drive their strategy and trading activity; unsurprisingly, the previously-hacked Astros were ranked first by ESPN in an annual ranking of sports teams based on their use of analytics. Per the report, other teams highly active in regard include the Tampa Bay Rays, Boston Red Sox, New York Yankees, and last but not least the Oakland Athletics—the team that arguably put Sabermetrics on the map.

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Sports is big business, and where money and competition collide—laws will be broken. This aptly describes the latest hack involving the St. Louis Cardinals and Houston Astros, though admittedly—it sounds more like a teaser for a Hollywood blockbuster.

For many of the MLBs harshest opponents, information security has been upgraded from a mere footnote to a new chapter in their playbooks. But for those teams embracing bleeding edge technologies whilst languishing in outdated data security, a fate similar to the Astros' awaits. Moneyball may have propelled baseball into the technological majors, but current advances in information science and big data analytics will see unprecedented uses of technology in the game, and indeed—in all sports.

Sampling Baseball's Big Data Players

The MLB is a profit machine and its constituent teams—like all businesses—strive to optimize their processes for agility/efficiency to remain competitive. This goes beyond sabermetrics to include all forms of data-driven continuous improvement.

Here are some examples of other franchises using big data to improve their bottom lines:

The Boston Red Sox uses big data to adjust ticket pricing based on game popularity throughout the year, as opposed to the traditional static pricing model

The Red Sox also aggregates and analyzes data around concession and food purchases, enabling them to create mechanisms for tracking fan purchasing behavior

The Milwaukee Brewers use Apache Spark to build marketing profiles of sporadic game attendees in hopes of turning them into season ticket holders

Unfortunately, big data technologies are often cited for their security shortcomings, and Apache Spark is no exception. To be fair, Hadoop infamously runs in non-secure mode out-of-the-box, and MongoDB certainly has security issues of its own. We hope that these and other data-dependent sports franchises have built up the appropriate security defenses for protecting their digital assets, especially since large, consolidated data repositoriesare highly-prized targets for both competitors and run-of-the-mill cyber attackers alike. And while the theft of player statistics and performance data can be strategically devastating on the field, the compromise of a franchise's customer and employee data, financial information, and other IT assets can be far more devastating in the long run.

Ultimately, sports franchises—like all big businesses these days—must adopt a digitally resilient posture to remain competitive. This means protecting the IT assets most critical to the enterprise accordingly. Whether we're talking about runs, batting averages, or software releases, strong information security shouldn't impede innovation—especially if baked-in to the continuous improvement process. To this end, UpGuard's platform for digitial resilience quantifies enterprise cyber risk in easy-to-grasp metrics for better strategic decision making and security.